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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

An Interpretable Index of Social Vulnerability to Environmental Hazards

Index-based measures of social vulnerability to environmental hazards are commonly modeled from composites of population-level risk factors. These models overlook individual context in communities' experiences of environmental hazards, producing metrics that may hinder spatial decision support for mitigating and responding to hazards. This paper introduces an interpretable, high-resolution model for generating an individual-oriented social vulnerability index (IOSVI) for the United States built on synthetic populations that couples individual and social determinants of vulnerability. The IOSVI combines an individual vulnerability index (IVI) that ranks individuals in an area’s synthetic population based on intersecting risk factors, with a social vulnerability index (SVI) based on the population’s cumulative distribution of IVI scores. Interpretability of the IOSVI procedure is demonstrated through examples of national, metropolitan, and neighborhood (census tract) level spatial variation in index scores and IVI themes, as well as an exploratory analysis examining risk factors affecting a specific sub-population (military veterans) in areas of high social and environmental vulnerability.

Tuccillo, Joe↗
DOE OSTI2024

Giant Modulation of Refractive Index from Picoscale Atomic Displacements

Abstract It is shown that structural disorder—in the form of anisotropic, picoscale atomic displacements—modulates the refractive index tensor and results in the giant optical anisotropy observed in BaTiS 3 , a quasi‐1D hexagonal chalcogenide. Single‐crystal X‐ray diffraction studies reveal the presence of antipolar displacements of Ti atoms within adjacent TiS 6 chains along the c ‐axis, and threefold degenerate Ti displacements in the a – b plane. 47/49 Ti solid‐state NMR provides additional evidence for those Ti displacements in the form of a three‐horned NMR lineshape resulting from a low symmetry local environment around Ti atoms. Scanning transmission electron microscopy is used to directly observe the globally disordered Ti a–b plane displacements and find them to be ordered locally over a few unit cells. First‐principles calculations show that the Ti a – b plane displacements selectively reduce the refractive index along the ab ‐plane, while having minimal impact on the refractive index along the chain direction, thus resulting in a giant enhancement in the optical anisotropy. By showing a strong connection between structural disorder with picoscale displacements and the optical response in BaTiS 3 , this study opens a pathway for designing optical materials with high refractive index and functionalities such as large optical anisotropy and nonlinearity.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Nonlinear Loss Engineering in Near‐Zero‐Index Bulk Materials

Transparent conducting oxides (TCOs) show unprecedented optical nonlinearities in the near infrared wavelength range, where the real part of their linear refractive index approaches zero. More specifically, the Kerr nonlinearities of these materials have sparked widespread attention due to their magnitude and speed. However, due to the absorptive nature of these nonlinear processes, it is of fundamental interest to further investigate the imaginary component of the nonlinear index. The present work studies the nonlinear optical absorption properties of aluminium‐doped zinc oxide (AZO) thin films in their near‐zero‐index (NZI) spectral window. It is found that the imaginary part of the refractive index is reduced under optical excitation such that the field penetration depth more than doubles. An optically induced shift of the NZI bandwidth of ≈120 nm for a pump intensity of 1.3 TW cm −2 is also demonstrated. Looking into the optically induced spectral redistribution of the probe signal, local net gain is recorded, which is ascribed to a nonlinear adiabatic energy transfer. The present study adds key information about the fundamental interplay between real and imaginary nonlinear indices in NZI media, while advancing parametric amplification as viable direction for loss compensation.

36 MATERIALS SCIENCE↗
DOE OSTI2022

An index to characterize gas‐solid and solid‐solid mixing from average volume fraction fields

Abstract A mixing index based on solid volume fraction fields is developed for gas‐solid flows. Conventional mixing indices are based on particle realizations of granular mixing and are applicable to experimental data or discrete element method simulations. However, these indices cannot be used as‐is for multifluid models, and an index for characterizing mixing in gas‐solid flows from continuous fields is needed. The performance of the new mixing index is tested in two applications. The first is a 3D simulation of the mixing of biomass and sand in a fluidized bed reactor, and the second is a 2D simulation of binary particle segregation in a fluidized bed. The simulations are performed using OpenFOAM®. The mixing index is used to quantify gas‐solid mixing using solid volume fractions and solid‐solid mixing using solid fractions. The formulation of conventional mixing indices is extended to be used with solid volume fractions fields, and methods for performance improvement are presented.

09 BIOMASS FUELS↗
DOE OSTI2026

Exploring Wildfire & Energy data toward State Prioritization Index (WESPI)

Energy infrastructure can both induce and suffer risks from wildfires ranging from direct damage to energy assets such as substations and power lines to Public Safety Power Shutoffs. Recent wildfire events underscore the need for data-driven approaches that help states and utilities proactively plan for wildfire risk. Existing national tools such as Federal Emergency Management Agency (FEMA)’s National Risk Index (NRI) are valuable for community hazard planning. However, they are less suited for energy infrastructure, as they emphasize population and building exposure rather than system vulnerabilities. In this paper, we explore relationships between energy and wildfire data and present a Wildfire-Energy State Prioritization Index (WESPI). Our methodology combines data from the US Forest Service’s Fire Simulation (FSIM) dataset with energy resilience metrics, historical fire incidents, and geospatial data on transmission lines and fire stations. Correlation analyses suggest that FSIM burn probability is more strongly associated with power outage metrics (ρ = 0.32) than NRI wildfire frequency, and counties with a greater density of fire stations experience more frequent, but less intense wildfires. We further leverage data for burn probability, transmission line density, and fire station density to develop a Wildfire-Energy State Prioritization Index (WESPI) to highlight counties where wildfire hazard, infrastructure exposure, and limited suppression capacity converge. The index provides a consistent, scalable framework for state energy offices and utilities to screen counties for vegetation management, optimization of outage management system deployment, and to inform wildfire mitigation plans.

Critical infrastructure↗
DOE OSTI2025

Drought adaptation index (DAI) based on BLUP as a selection approach for drought-resilient switchgrass germplasm

This study introduces a Drought Adaptation Index (DAI), derived from Best Linear Unbiased Prediction (BLUP), as a method to assess drought resilience in switchgrass (Panicum virgatum L.). A panel of 404 genotypes was evaluated under drought-stressed (CV) and well-watered (UC) conditions over four consecutive years (2019–2022). BLUP-estimated biomass yields were used to calculate the DAI, which enabled classification of genotypes into four adaptation groups: very well-adapted, well-adapted, adapted, and unadapted. The DAI was compared with conventional drought tolerance indices, including the Stress Susceptibility Index (SSI), Stress Tolerance Index (STI), Geometric Mean Productivity (GMP), and Yield Stability Index (YSI). Correlation analyses demonstrated strong agreement between DAI and these indices, supporting its validity and consistency. Biplot analyses using the Genotype plus Genotype-by-Environment Interaction (GGE) and Additive Main Effects and Multiplicative Interaction (AMMI) models revealed significant genotype-by-environment interactions (GEI) and identified J222.A, J463.A, and J295.A. A as high-performing genotypes, with J222.A exhibiting greater yield stability across treatments and years. Additionally, DAI isoline curves provided a graphical representation of differential genotype performance under drought and control conditions. These visualizations aided in distinguishing genotypes with stable and superior biomass yield across contrasting environments. Overall, the BLUP-based DAI is a robust and practical selection tool that improves the accuracy of identifying drought-resilient, high-yielding switchgrass genotypes. Its integration into breeding programs offers a comprehensive framework for improving biomass productivity and stress adaptation under variable climatic conditions. The application of DAI supports the development of climate-resilient cultivars and contributes to sustainable bioenergy and forage production systems.

BLUP↗
DOE OSTI2023

Estimating Field-Level Perennial Bioenergy Grass Biomass Yields Using the Normalized Difference Red-Edge Index and Linear Regression Analysis for Central Virginia, USA

We investigated the indicative power of the normalized difference red-edge index (NDRE) for estimating field-level perennial bioenergy grass biomass yields utilizing Sentinel-2 imagery and a linear regression model as a rapid, cost-effective method for biomass yield estimations for bioenergy. We used 2019 data from three study sites containing mature perennial bioenergy grass stands in central Virginia, USA. Of the simulated daily NDRE values based on the temporally weighted averaging of two temporal neighbors, we found the strongest index–yield correlation on 11 August (R = 0.85). We estimated the perennial bioenergy grass biomass yields for (1) all sites using the data pooled from the three sites (all-site estimation) and (2) each site using the data pooled from the other two sites (cross-site estimation). The estimated field-level perennial bioenergy grass biomass yields strongly correlated with the recorded yields (average R2 = 0.76), with a root mean square error (RMSE) of 1.5 Mg/ha and a mean absolute error (MAE) of 1.2 Mg/ha for the all-site estimation. For the cross-site estimation, the site with diverse perennial grass types had the weakest correlation (R2 = 0.44) of the sites, indicating a difficulty in accounting for heterogeneous index–yield relationships in a single model. In addition to identifying a strong indicative power of the NDRE for estimating the overall perennial bioenergy grass biomass yields at a field level, the findings from this study call for an analysis across multiple perennial grasses and a comparison using multiple sites to understand (1) if the indicative power of the index shifts from the biomass of the specific perennial bioenergy grass type to the overall biomass during the growing season and (2) the level of perennial bioenergy grass heterogeneity that may hinder the remotely sensed biomass yield estimation using a single model.

09 BIOMASS FUELS↗
DOE OSTI2025

The superconformal index and black hole instabilities

The superconformal index of $\mathcal{N}$ = 4 supersymmetric Yang-Mills theory with gauge group U(N) has provided powerful insights into the entropy of supersymmetric black holes in AdS 5 × S 5 , including some sub-leading logarithmic and non-perturbative corrections. Recently, the phase space of supersymmetric solutions has been argued to contain configurations other than the asymptotically AdS 5 black hole. Such configurations include the so-called grey galaxies where the black hole at the center is surrounded by a gas of gravitons. By numerically evaluating the superconformal index of $\mathcal{N}$ = 4 supersymmetric Yang-Mills at small values of N, we detect systematic deviations from the entropy of black holes with two distinct angular momenta. We find that the giant graviton expansion of the index is a numerically efficient way of evaluating the index that complements the direct character evaluation and allows for explicit access to N ≤ 15 with up to two giant gravitons in the expansion. We find it remarkable that a supersymmetric quantity in field theory, usually thought of as a rigid counting observable, indeed contains information about different phases in the space of supersymmetric solutions on the gravity side.

AdS-CFT correspondence↗
DOE OSTI2024

Gravitational index of the heterotic string

The fundamental heterotic string has a tower of BPS states whose supersymmetric index has an exponential growth in the charges. We construct the saddle-point of the gravitational path integral corresponding to this index. The saddle-point configuration is a supersymmetric rotating non-extremal Euclidean black hole. This configuration is singular in the two-derivative theory. We show that the addition of higher-derivative terms in four-dimensional N = 2 supergravity resolves the singularity. In doing so, we extend the recently-developed “new attractor mechanism” to include the effect of higher-derivative terms. Remarkably, the one-loop, four-derivative F-term contribution to the prepotential leads to a precise match of the gravitational and microscopic index. We also comment, using the effective theory near the horizon, on the possibility of a string-size near-extremal black hole. Our results clarify the meaning of different descriptions of this system in the literature. The thermal state transitions to a winding condensate and a gas of strings without ever reaching a small black hole, while the index is captured by the rotating Euclidean black hole solution and is constant and thus smoothly connected to the microscopic ensemble.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Thermalization of the Kerr index of refraction in acetone and methanol using femtosecond pump-probe scattering spectroscopy

Femtosecond time-resolved pump-probe scattering is used to temporally investigate the index thermalization Δn(t) of the molecular motions associated with the Kerr nonlinear index n 2 . This is done using an intense 300 fs 1034 nm pump pulse and temporally probed by a 517 nm and supercontinuum pulse in acetone and methanol. The optically pumped molecular states change the index of refraction and through the processes of Raman and Rayleigh scattering are shown to engage in a 4-step energy relaxation process. Here, the pump first initiates the Kerr effect as well as populate resonant vibrational molecular motions, which act as a “mother” energy state. The electronic component of the Kerr effect is shown to couple with these vibrational modes through the process of Born-Oppenheimer coupling, which can be measured through the Raman scattering of the probe. The “mother” coupled state then decays into “daughter” anharmonic non-resonant states, which then further decay into “granddaughter” and thermal bath states. The population of these states alter the index of refraction in time, Δn(t), and can be measured through the changing in the probe beam’s Rayleigh scattering. This thermalization process takes ~5.5 ps in acetone and ~3.7 ps in methanol. The scattering signals from each Δn(t) thermalization stage in the localized region, (“mother”, to “daughter”, to “granddaughter”, to the bath states, to the ground state), are fitted to theoretical decay equations that show the rise and fall times of the energy decay routes.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

A Denoising Autoencoder for Improved Kikuchi Pattern Quality and Indexing in Electron Backscatter Diffraction

The rapid collection and indexing of electron diffraction patterns as produced via electron backscatter diffraction (EBSD) has enabled crystallographic orientation and structural determination, as well as additional property-determining strain and dislocation density information with increasing speed, resolution, and efficiency. Pattern indexing quality is reliant on the noise of the collected electron diffraction patterns, which is often convoluted by sample preparation and data collection parameters. EBSD acquisition is sensitive to many factors and thus can result in low confidence index (CI), poor image quality (IQ), and improper minimization of fit, which can result in noisy datasets and misrepresent the microstructure. In an attempt to enable both higher speed EBSD data collection and enable greater orientation fit accuracy with noisy datasets, an image denoising autoencoder was implemented to improve pattern quality. Here, we show that EBSD data processed through the autoencoder results in a higher CI, IQ, and a more accurate degree of fit. In addition, using denoised datasets in HR-EBSD cross correlative strain analysis can result in reduced phantom strain from erroneous calculations due to the increased indexing accuracy and improved correspondence between collected and simulated patterns.

36 MATERIALS SCIENCE↗
DOE OSTI2026

A theoretical index for understanding distinct land relative humidity trends in observations, reanalyses, and models

Land surface relative humidity (RH) is a key variable in the coupled land–atmosphere system that profoundly influences terrestrial hydroclimate and ecosystems. Yet historical changes in land RH are not well understood due to limited observations, biased reanalyses, and the lack of a framework for interpreting RH changes under multiple influencing factors. Here, we show that the spatiotemporal variability of land RH and its distinct historical trends among observations, reanalyses, and Earth system models are captured by a simple index based on the ratio of precipitation (P) to a modified potential evapotranspiration formulated independently of RH (PET°). The index provides a physical calibration of biased land RH in reanalyses and a quantitative framework for interpreting land RH changes. Over 1973–2024, land RH has decreased substantially, owing to the intrinsic rise in PET° with temperature and little increase in land precipitation. Reanalyses overestimate the observed RH decrease, consistent with exaggerated surface warming and precipitation decline. The index captures this coherent bias and enables a calibration using observed precipitation and temperature. Models simulate a wide range of land RH trends, but nearly all runs underrepresent the historical drying. The index captures the model spread and discrepancy and attributes them to contributions of precipitation and PET°. Weaker land RH decreases in models arise mainly from weaker subtropical precipitation declines, linked to muted intensification of subtropical highs and biased subtropical climatology. The model–observation discrepancy is unlikely explained by internal variability, implying model underestimation of forced RH decrease and a drier land future than current projections.

Earth system models↗
DOE OSTI2023

A phenomenological wobbling model for isolated pulsars and the braking index

ABSTRACT An isolated pulsar is a rotating neutron star possessing a very high magnetic dipole moment, thus providing a powerful radiating mechanism. These stars loose rotational energy E through various processes, including a plasma wind originating from a highly magnetized magnetosphere and the emission of magnetic dipole radiation (MDR). Such phenomena produce a time decreasing angular velocity Ω(t) of the pulsar that is usually quantified in terms of its braking index. Although these mechanisms are widely acknowledged as the primary drivers of the spin evolution of isolated pulsars, it is plausible that other contributing factors influencing this effect have yet to be comprehensively investigated. Most of young isolated pulsars present a braking index different from that given by the MDR and plasma wind processes. Working in the weak field (Newtonian) limit, we take in this work a step forward in describing the evolution of such a system by allowing the star’s shape to wobble around an ellipsoidal configuration as a backreaction effect produced by its rotational deceleration. It is assumed that an internal damping of the oscillations occurs, thus introducing another form of energy loss in the system, and this phenomenon may be related to the deviation of the braking index from the models based on $\dot{E} \sim -\Omega ^4$ predictions. Numerical calculations suggest that the average braking index for typical isolated pulsars can be thus explained by a simple phenomenological model.

Araujo, E. C. A. (ORCID:0000000213520879)↗
DOE OSTI2021

Achieving extreme light confinement in low-index dielectric resonators through quasi-bound states in the continuum

Obtaining large field enhancement in low-refractive-index dielectric materials is highly relevant to many photonic and quantum optics applications. However, confining light in these materials is challenging, owing to light leakage through coupling to continuum modes in the surrounding environment. Here, we investigate the possibility of achieving high quality factors in low-index dielectric resonators through the bound states in the continuum (BIC). Our simulations demonstrate that destructive interference between leaky modes can be achieved by tuning the geometrical parameters of the resonator arrays, leading to the emergence of quasi-BIC in resonators that have a small index contrast to the underlying substrates. The resultant large field enhancement gives rise to giant quality factors and Purcell effects. By introducing vertical mirror symmetry, the quasi-BIC can be tuned into an ideal BIC. In addition, the quasi-BIC can modify the emission patterns of the coupled emitters, rendering highly directional and focused far-field emission. These findings may provide a path for the practical implementation of photonic and quantum devices based on low-index dielectric materials.

42 ENGINEERING↗
DOE OSTI2025

Eureka: Enabling Fine-Grained Access and Range Queries on Compressed Scientific Data via Data-Index Co-Compression

Handling large-scale scientific data in high-performance computing (HPC) environments poses significant challenges, including excessive I/O, high storage costs, and slow query performance. Traditional approaches often require full data decompression and scans, making them impractical for real-time or interactive analysis. To address these limitations, we introduce Eureka, a unified data-index co-compression framework that enables fine-grained access and efficient range queries on compressed scientific datasets. Eureka integrates spatial domain decomposition with block-wise error-bounded lossy compression to support selective decompression. It constructs a hierarchical AVL-tree index during compression to capture block-level value ranges, enabling fast pruning during query execution. To reduce metadata overhead, the index itself is also compressed while ensuring recall-preserving results. Experiments on six diverse HPC simulation datasets show that Eureka achieves up to 25x data compression and over 300x index compression, surpassing state-of-the-art compressors such as SZ3 and ZFP in rate-distortion performance. Additionally, Eureka delivers over 30x speedup for low-selectivity range queries, making it a scalable and efficient solution for modern scientific data analysis.

Yan, Ning↗
DOE OSTI2022

Low refractive index OLEDs for practical high-efficiency outcoupling. Final report

Improving OLED light extraction is a significant on-going challenge for the OLED lighting industry. The goal of this program was to explore the potential to improve internal light extraction in a manufacturable way by lowering the refractive index of the OLED stack through dilution with an electrically-inert, low refractive index molecule. We accomplished this goal, identifying a small molecule that can be co-evaporated in the hole transport layer of OLEDs at high loading to reduce the refractive index by 0.2-0.3 refractive index units without degrading charge transport. Implementing this dilution molecule in the hole transport layer of a range of single and multi-stack OLEDs, we demonstrated the ability to improve their internal light extraction by up to ~35% without increasing their drive voltage or reducing their operational lifetime. Importantly, these findings extend to state-of-the-art device architectures with proprietary OLED materials.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

The Workforce Readiness Index: A Local and Regional Assessment Tool for Energy Sector Preparedness

Building up a workforce that is properly trained and adequately sized is essential to ensuring that the deployment of energy generation sources in the United States meets future energy demand. Workforce development to support supply chain or large infrastructure investments typically occurs at a local level. However, there is a critical gap in understanding where and to what extent regional workforces are equipped to meet the needs of an energy industry. The Workforce Readiness Index ("the index") was developed to assess and compare energy sector workforce readiness across the United States at the county level to provide granular information to various stakeholders such as industry members, state decision makers, and training program developers. Workforce readiness is defined as the ability to recruit from the general labor market, transition workers with comparable skill sets, and train a workforce using scalable or existing training programs near a specific location. Therefore, the index evaluates readiness levels based on the likelihood that a county possesses the workforce development infrastructure needed to support the occupations required by an energy-related industry or sector. Furthermore, the index offers a standardized yet flexible approach that captures regional variations and highlights local strengths and challenges.

17 WIND ENERGY↗
DOE OSTI2022

Learning infinite-horizon average-reward restless multi-action bandits via index awareness

We consider the online restless bandits with average-reward and multiple actions, where the state of each arm evolves according to a Markov decision process (MDP), and the reward of pulling an arm depends on both the current state of the corresponding MDP and the action taken. Since finding the optimal control is typically intractable for restless bandits, existing learning algorithms are often computationally expensive or with a regret bound that is exponential in the number of arms and states. In this paper, we advocate \textit{index-aware reinforcement learning} (RL) solutions to design RL algorithms operating on a much smaller dimensional subspace by exploiting the inherent structure in restless bandits. Specifically, we first propose novel index policies to address dimensionality concerns, which are provably optimal. We then leverage the indices to develop two low-complexity index-aware RL algorithms, namely, (i) GM-R2MAB, which has access to a generative model; and (ii) UC-R2MAB, which learns the model using an upper confidence style online exploitation method. We prove that both algorithms achieve a sub-linear regret that is only polynomial in the number of arms and states. A key differentiator between our algorithms and existing ones stems from the fact that our RL algorithms contain a novel exploitation that leverages our proposed provably optimal index policies for decision-makings.

Xiong, Guojun↗